#!/usr/bin/env python
# coding=utf-8
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
"""Paired sequences from the Observed Antibody Space database"""
import datasets
import os
import csv

_CITATION = """\
@article{Olsen_Boyles_Deane_2022, 
title={Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences}, 
volume={31}, rights={© 2021 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.}, 
ISSN={1469-896X}, DOI={10.1002/pro.4205}, 
number={1}, journal={Protein Science}, author={Olsen, Tobias H. and Boyles, Fergus and Deane, Charlotte M.}, 
year={2022}, pages={141–146}, language={en} }

"""
_DESCRIPTION = """\
Paired heavy and light chain antibody sequences for multiple species.
"""

_HOMEPAGE = "https://opig.stats.ox.ac.uk/webapps/oas/"

_LICENSE = "cc-by-4.0"
_BASE_URL = "https://aws-hcls-ml.s3.amazonaws.com/oas-paired-sequence-data/raw/"

# _URLS = {
#     "human": _BASE_URL + "human.tar.gz",
#     "rat_SD": _BASE_URL + "rat_SD.tar.gz",
#     "mouse_BALB_c": _BASE_URL + "mouse_BALB_c.tar.gz",
#     "mouse_C57BL_6": _BASE_URL + "mouse_C57BL_6.tar.gz",
# }
_FEATURES = datasets.Features(
    {
        "sequence_alignment_aa_heavy": datasets.Value("string"),
        "cdr1_aa_heavy": datasets.Value("string"),
        "cdr2_aa_heavy": datasets.Value("string"),
        "cdr3_aa_heavy": datasets.Value("string"),
        "sequence_alignment_aa_light": datasets.Value("string"),
        "cdr1_aa_light": datasets.Value("string"),
        "cdr2_aa_light": datasets.Value("string"),
        "cdr3_aa_light": datasets.Value("string"),
    }
)


class OasPairedSequenceData(datasets.GeneratorBasedBuilder):
    """OAS paired sequence data."""

    VERSION = datasets.Version("1.2.0")
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="human", version=VERSION, description="human"),
        datasets.BuilderConfig(name="rat_SD", version=VERSION, description="rat_SD"),
        datasets.BuilderConfig(
            name="mouse_BALB_c", version=VERSION, description="mouse_BALB_c"
        ),
        datasets.BuilderConfig(
            name="mouse_C57BL_6", version=VERSION, description="mouse_C57BL_6"
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=_FEATURES,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    # def _split_generators(self, dl_manager):
    #     urls = _URLS[self.config.name]
    #     data_dir = dl_manager.download_and_extract(urls)
    #     return [
    #         datasets.SplitGenerator(
    #             name=datasets.Split.TRAIN,
    #             gen_kwargs={
    #                 "filepath": os.path.join(data_dir),
    #                 "split": "train",
    #             },
    #         ),
    #     ]

    # def _generate_examples(self, filepath, split):
    #     table = pd.read_parquet(filepath)
    #     for key, row in enumerate(table.itertuples()):
    #         if key == 0:
    #             continue
    #         yield key, {
    #             "sequence_alignment_aa_heavy": row[1],
    #             "cdr1_aa_heavy": row[2],
    #             "cdr2_aa_heavy": row[3],
    #             "cdr3_aa_heavy": row[4],
    #             "sequence_alignment_aa_light": row[5],
    #             "cdr1_aa_light": row[6],
    #             "cdr2_aa_light": row[7],
    #             "cdr3_aa_light": row[8],
    #         }

    def _split_generators(self, dl_manager):
        data_unit_file = os.path.join(
            os.getcwd(), "data_units", self.config.name + ".txt"
        )
        with open(data_unit_file, "r") as f:
            urls = [
                os.path.join(_BASE_URL, self.config.name, line.strip()) for line in f
            ]
        data_files = dl_manager.download_and_extract(urls)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": data_files,
                    "split": "train",
                },
            ),
        ]

    def _generate_examples(self, filepaths):
        for filepath in filepaths:
            with open(filepath, "r") as f:
                reader = csv.reader(f, delimiter=",")
                for key, row in enumerate(reader):
                    if key < 2:
                        continue
                    else:
                        yield key - 2, {
                            "sequence_alignment_aa_heavy": row[14],
                            "cdr1_aa_heavy": row[37],
                            "cdr2_aa_heavy": row[41],
                            "cdr3_aa_heavy": row[47],
                            "sequence_alignment_aa_light": row[113],
                            "cdr1_aa_light": row[136],
                            "cdr2_aa_light": row[140],
                            "cdr3_aa_light": row[146],
                        }